Abstract
BackgroundGraph drawing is an integral part of many systems biology studies, enabling visual exploration and mining of large-scale biological networks. While a number of layout algorithms are available in popular network analysis platforms, such as Cytoscape, it remains poorly understood how well their solutions reflect the underlying biological processes that give rise to the network connectivity structure. Moreover, visualizations obtained using conventional layout algorithms, such as those based on the force-directed drawing approach, may become uninformative when applied to larger networks with dense or clustered connectivity structure.MethodsWe implemented a modified layout plug-in, named Multilevel Layout, which applies the conventional layout algorithms within a multilevel optimization framework to better capture the hierarchical modularity of many biological networks. Using a wide variety of real life biological networks, we carried out a systematic evaluation of the method in comparison with other layout algorithms in Cytoscape.ResultsThe multilevel approach provided both biologically relevant and visually pleasant layout solutions in most network types, hence complementing the layout options available in Cytoscape. In particular, it could improve drawing of large-scale networks of yeast genetic interactions and human physical interactions. In more general terms, the biological evaluation framework developed here enables one to assess the layout solutions from any existing or future graph drawing algorithm as well as to optimize their performance for a given network type or structure.ConclusionsBy making use of the multilevel modular organization when visualizing biological networks, together with the biological evaluation of the layout solutions, one can generate convenient visualizations for many network biology applications.
Highlights
Graph drawing is an integral part of many systems biology studies, enabling visual exploration and mining of large-scale biological networks
Such a test-and-trial strategy often neglects the biological relevance of the layout solutions, as well as requires bioinformatics skills or resources to allow experimenting with several algorithms, many of which are not implemented as user-friendly software packages
Biological evaluation procedure To facilitate biological evaluation of the layout algorithms and their solutions, we developed and implemented an additional plug-in for Cytoscape, named Biological Evaluation plug-in, for which implementation, source-code and user-instructions are freely available from website [35]
Summary
Graph drawing is an integral part of many systems biology studies, enabling visual exploration and mining of large-scale biological networks. There exists a wide variety of advanced network layout algorithms that seek to place connected nodes of a graph close to each other. These layout algorithms are designed for a particular network type, such as gene regulatory networks or signalling pathways [11,12], metabolic pathways or biochemical networks [13,14,15], or phylogenetic networks [16]. There exists no universal layout solution, and a practical strategy involves trying out multiple layout algorithms a number of times to see which one best arranges a given network [6,20]. Such a test-and-trial strategy often neglects the biological relevance of the layout solutions, as well as requires bioinformatics skills or resources to allow experimenting with several algorithms, many of which are not implemented as user-friendly software packages
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